New Serological Measures of Infectious Disease Transmission Intensity

传染病传播强度的新血清学测量方法

• 批准号: 9275314
• 负责人: Benjamin F Arnold
• 金额: $ 14.22万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-06-18 至 2020-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9275314
• 关键词: Age; Antibodies; Antibody Response; Antigens; Applied Research; Area; Biological Assay; Biometry; Blood; California; Campylobacter; Caregivers; Centers for Disease Control and Prevention (U.S.); Child; Cluster randomized trial; Collaborations; Communicable Diseases; Computer software; Country; Cross-Sectional Studies; Cryptosporidium; Cryptosporidium parvum; Data; Development; Diagnostic tests; Diarrhea; Disease; Doctor of Philosophy; Entamoeba histolytica; Enteral; Environment; Epidemiologic Methods; Epidemiologist; Epidemiology; Faculty; Family; Filarial Elephantiases; Future; Giardia; Goals; Haiti; Handwashing; Health; Immune response; Immunologist; Immunology; Individual; Infection; Infectious Disease Epidemiology; Infectious Disease Immunology; Infectious Diseases Research; International; Intervention; Intervention Studies; Kenya; Literature; Machine Learning; Measles; Measurement; Measures; Mentors; Methodology; Methods; Modeling; Monitor; Mumps; Outcome; Pharmaceutical Preparations; Play; Population; Public Health; Recording of previous events; Reporting; Research; Research Personnel; Role; Rubella; Running; Salmonella; Sanitation; Serological; Seroprevalences; Source; Spottings; Statistical Methods; Statistical Models; Survival Analysis; Tanzania; Testing; Time; Training; Translating; Translations; Universities; Vibrio cholerae; Viral; Water; Work; base; career; cohort; comparison group; cost; disease transmission; drinking water; effectiveness measure; enteric pathogen; enterotoxigenic Escherichia coli; experience; flexibility; high risk population; improved; intervention effect; intervention program; low income country; member; multidisciplinary; neglected tropical diseases; novel; novel strategies; open source; pathogen; professor; programs; public health intervention; public health relevance; research study; response; semiparametric; seroconversion; seropositive; skills; statistics; theories; therapy design; tool; transmission process; user-friendly

 DESCRIPTION (provided by applicant): Candidate: Benjamin Arnold I am an epidemiologist at the University of California, Berkeley. I completed my MA in Biostatistics and a PhD in Epidemiology from UC Berkeley in 2009. Since then, I have worked as an epidemiologist in Professor Jack Colford's group. The opportunity to work as the coordinating epidemiologist for a touchstone, multi-country cluster randomized trial - combined with the addition of two children to my family - led me to delay my academic career. I am now ready to restart my career progress toward independent investigator status. My long-term career goal is to become a leader in the application of novel statistical methods to target and evaluate interventions that reduce the burden of enteric infections and neglected tropical diseases (NTDs) in low-income countries. This research focus and career objective build from my experience and from a growing collaboration with Dr. Patrick Lammie at the US Centers for Disease Control (CDC) that started in 2013 and has introduced me to seroepidemiologic research. My background in epidemiologic methods, biostatistics, and international field research makes me uniquely qualified to make significant contributions to infectious disease epidemiology at the interface between recent advances in statistical methodology and serological assays. Environment: University of California, Berkeley To achieve my career goal, I have developed a training and mentoring plan that focuses on recent advances in statistics (semi-parametric estimation theory and machine learning) and on infectious disease immunology. These are two areas where additional training will open up significant and unique opportunities for me to make meaningful contributions to seroepidemiologic research, and will enable me to launch an independent career as a productive faculty member at UC Berkeley. I have assembled a multidisciplinary mentoring team of senior investigators in biostatistics and immunology to support my training, research, and career objectives. Mark van der Laan (primary mentor, biostatistics) will guide my training in semi-parametric methods and machine learning. Alan Hubbard (co-mentor, biostatistics) will guide my translation of the methodology to applications for enteric pathogens and NTDs. Patrick Lammie (co-mentor at CDC, immunology) will guide my immunology training and research with his expertise in the immunology of enteric pathogens and NTDs Research: New Serological Measures of Infectious Disease Transmission Background: Recent advances in multiplex antigen assays have led to the development of low-cost and sensitive methods to measure enteric pathogens and neglected tropical diseases (NTDs). There have not been commensurate advances in the statistical methods used to derive measures of transmission intensity from antibody response. Translating antibody response into metrics of transmission intensity is a key step from a public health perspective because it enables us to target intervention programs to the populations most in need and then measure the effectiveness of those programs. Aims and Methods: The overarching goal of this research is to develop a methodologic framework to translate antibody response measured in cross-sectional surveys into measures of transmission intensity for enteric pathogens (7 included in the study, e.g., Cryptosporidium parvum, enterotoxigenic E. coli) and neglected tropical diseases (principal focus: lymphatic filariasis). We approach this goal from two novel perspectives. In Aim 1, we draw on the "peak shift" phenomenon for infectious diseases, and hypothesize that changes in transmission will be detectable in the age-specific antibody response curve. At lower transmission, antibody levels should decline across all ages due to fewer and less frequent active infections, leading to an overall shift in the age-specific response curve. We will evaluate the approach by comparing antibody response curves for young children with different exposures (improved vs. unimproved drinking water for enteric pathogens; pre- versus post- mass drug administration for lymphatic filariasis) in large, well characterized cohorts in Kenya, Tanzania, and Haiti. In Aim 2, we will develop semi-parametric methods to estimate the force of infection (seroconversion rate) from seroprevalence data for pathogens where seroreversion is possible, using lymphatic filariasis as an example. Our new approach marks a significant advance over previous work in this area by making few modeling assumptions and by allowing for the flexible control of confounding between comparison groups. We will evaluate the approach in Haiti by measuring the effect of mass drug administration on the force of infection for lymphatic filariasis For all of the methods, we will create user-friendly, open source software to accelerate translation to applied research. The Future: This mentored training and research plan represents a natural next step for me on a productive and collaborative path to independence at UC Berkeley. It will set the stage for a broader R01-level research portfolio that applies the newly developed methods to primary research studies that evaluate the impact of interventions on enteric infections, and help target and monitor global elimination efforts for NTDs.

 描述（由申请人提供）： 候选人：本杰明·阿诺德 我是加州大学伯克利分校的流行病学家。2009年，我在加州大学伯克利分校完成了生物统计学硕士学位和流行病学博士学位。从那时起，我在杰克·科尔福德教授的小组里担任流行病学家。有机会作为一个试金石，多国集群随机试验的协调流行病学家-再加上两个孩子加入我的家庭-导致我推迟了我的学术生涯。我现在准备重新开始我的职业生涯，争取独立调查员的地位。 我的长期职业目标是成为应用新型统计方法的领导者，以针对和评估降低低收入国家肠道感染和被忽视的热带病（NTD）负担的干预措施。这一研究重点和职业目标建立在我的经验和与帕特里克Lammie博士在美国疾病控制中心（CDC）的日益增长的合作基础上，该合作始于2013年，并将我引入血清流行病学研究。我在流行病学方法，生物统计学和国际实地研究的背景使我唯一有资格在统计方法和血清学检测的最新进展之间的界面上为传染病流行病学做出重大贡献。 环境：加州大学伯克利分校 为了实现我的职业目标，我制定了一个培训和指导计划，重点是统计学（半参数估计理论和机器学习）和传染病免疫学的最新进展。这是两个领域，额外的培训将为我开辟重要和独特的机会，使有意义的贡献，血清流行病学研究，并将使我能够启动一个独立的职业生涯，作为一个富有成效的教师在加州大学伯克利分校。 我组建了一个由生物统计学和免疫学高级研究人员组成的多学科指导团队，以支持我的培训，研究和职业目标。Mark货车der Laan（生物统计学初级导师）将指导我进行半参数方法和机器学习的培训。Alan Hubbard（生物统计学共同导师）将指导我将该方法翻译成肠道病原体和NTD的应用。帕特里克拉米（共同导师在疾病预防控制中心，免疫学）将指导我的免疫学培训和研究与他的专业知识在肠道病原体和NTD的免疫学 研究：传染病传播的新血清学措施 背景资料：多重抗原检测的最新进展导致了低成本和灵敏度的方法来测量肠道病原体和被忽视的热带病（NTD）的发展。用于从抗体应答中得出传播强度测量值的统计方法尚未取得相应的进展。从公共卫生的角度来看，将抗体反应转化为传播强度的指标是一个关键步骤，因为它使我们能够将干预计划瞄准最需要的人群，然后衡量这些计划的有效性。 目的和方法：本研究的总体目标是开发一种方法学框架，将横断面调查中测量的抗体应答转化为肠道病原体传播强度的测量（研究中包括7种，例如，隐孢子虫、肠寄生性E.大肠杆菌）和被忽视的热带疾病（主要重点：淋巴丝虫病）。我们从两个新的角度来实现这一目标。在目标1中，我们利用传染病的“峰移”现象，并假设传播的变化将在年龄特异性抗体反应曲线中检测到。在较低的传播，抗体水平应下降，在所有年龄，由于更少和更不频繁的活动性感染，导致整体移动的年龄特异性反应曲线。我们将在肯尼亚、坦桑尼亚和海地的大型、特征明确的队列中，通过比较不同暴露（改善与未改善的饮用水用于肠道病原体;大规模药物给药前与后用于淋巴丝虫病）的幼儿的抗体应答曲线来评估该方法。 在目标2中，我们将开发半参数方法，以淋巴丝虫病为例，根据血清阳性率数据估计可能发生血清转化的病原体的感染力（血清转化率）。我们的新方法标志着一个显着的进步，在这方面的工作，使一些建模假设，并允许灵活控制比较组之间的混淆。我们将通过测量大规模药物管理对淋巴丝虫病感染力的影响来评估海地的方法。对于所有方法，我们将创建用户友好的开源软件，以加速转化为应用研究。 未来：这个指导的培训和研究计划代表了我在加州大学伯克利分校独立的生产和协作道路上的自然下一步。它将为更广泛的R 01级研究组合奠定基础，将新开发的方法应用于主要研究，评估干预措施对肠道感染的影响，并帮助确定目标和监测全球消除NTD的努力。